[Corpora-List] Open Research Position (M.S. / Ph.D. / post-doc): Analyzing Routine Activities for Crime Prediction

Adam Kilgarriff adam at lexmasterclass.com
Tue Apr 22 20:39:00 CEST 2014


If a clever system can predict who is going to predict a crime - with good, but far from 100%, accuracy, is the use it

a) rational policing practice

b) discriminatory to use that information?

Seems to me, it's both.

Marek says
> But there are definitely many ways to abuse this technology as well.

I don't feel abuse is the main issue. Any use of it is discriminatory. Should we trade off? Tough question.

Adam

On 22 April 2014 11:34, Marek Rei <marek.rei at gmail.com> wrote:


> Here's an interesting article about how Chicago police is already applying
> such technology (in somewhat troubling ways):
>
>
> http://www.theverge.com/2014/2/19/5419854/the-minority-report-this-computer-predicts-crime-but-is-it-racist
>
> I wouldn't say crime prediction technology by itself is evil, it's more a
> question of how it's used. For example, I wouldn't have a problem with a
> system that can prioritise a large list of likely suspects after a crime
> has been committed, or is able to flag a social media message calling for a
> hate crime. But there are definitely many ways to abuse this technology as
> well.
>
> Marek
>
>
>
> On Tue, Apr 22, 2014 at 10:55 AM, Christian Pietsch <
> chr.pietsch at googlemail.com> wrote:
>
>> Hi Matthew,
>>
>> so you want to build a heuristic precrime detector based on routine
>> activities observed on social networks. Does that mean that if, say, I
>> tend to update my status at the same time as some terrorist in your
>> training set, your software will label me as a likely terrorist and
>> put me on a no-fly list? Will I get a chance to prove my innocence?
>>
>> When you have some spare time, try to watch Minority Report. Or did
>> this movie inspire your project? Then you must have misunderstood its
>> message.
>>
>> Your suspect
>> Christian
>>
>>
>> On Mon, Apr 21, 2014 at 11:34:11AM -0400, Matthew Gerber wrote:
>> > Hello,
>> >
>> > A new research position has opened within our lab, and we are seeking
>> M.S.,
>> > Ph.D., and post-doc researchers.
>> >
>> > One-sentence summary: We are mining social media for indicators of
>> > individual routine activities for the purpose of improved crime
>> prediction.
>> >
>> > Longer summary: This project focuses on the spatiotemporal prediction of
>> > localized attacks carried out against individuals in urban areas. We
>> view
>> > an attack as the outcome of a point process governed by the interaction
>> of
>> > attackers, targets, and the physical environment. Our ultimate goal is
>> to
>> > predict future outcomes of this process in order to increase the
>> security
>> > of human populations and U.S. assets and interests. However, achieving
>> this
>> > goal requires a deeper understanding of how attack outcomes correlate
>> with
>> > the routine activities of individuals in an area. The proposed research
>> > will generate this understanding and in doing so will answer questions
>> such
>> > as the following: What are the dimensions along which individuals’
>> > activities should be quantified for the purpose of attack prediction?
>> How
>> > can measurements along these dimensions be taken automatically and with
>> > minimal expense (e.g., via social media)? What are the implications of
>> such
>> > measurements for attack prediction performance? Subsuming these
>> questions
>> > is the issue of geographic variation: do our answers change when moving
>> > from a major U.S. city to a major U.K. city? There has been plenty of
>> > previous work on spatiotemporal attack prediction (see our Asymmetric
>> > Threat<
>> http://ptl.sys.virginia.edu/ptl/projects/asymmetric-threat-prediction
>> >project);
>> > however, these basic questions remain unanswered, leaving a
>> > substantial gap in our understanding of attack processes and their
>> > relationships with individuals’ routine activities.
>> >
>> > More information can be found
>> > here<
>> http://ptl.sys.virginia.edu/ptl/projects/routine-activities-analysis-for-crime-prediction
>> >
>> > .
>> >
>> > Sincerely,
>> >
>> > Matthew S. Gerber, Ph.D.
>> > Research Assistant Professor
>> > Department of Systems and Information Engineering
>> > University of Virginia
>>
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-- ======================================== Adam Kilgarriff <http://www.kilgarriff.co.uk/> adam at lexmasterclass.com Director Lexical Computing Ltd<http://www.sketchengine.co.uk/>

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